Global spending on artificial intelligence is projected to reach $2.52 trillion in 2026, marking a sharp 44 per cent year-on-year increase, according to a new report released on Thursday.
The report highlights that AI adoption is increasingly being shaped by organisational readiness and human capital maturity, rather than investment size alone. According to Gartner Distinguished VP Analyst John-David Lovelock, enterprises with greater experiential maturity are now prioritising proven business outcomes over speculative AI potential.
A significant portion of the projected growth will be driven by foundational AI investments. Spending on AI-optimised servers alone is expected to rise by 49 per cent, accounting for nearly 17 per cent of total AI expenditure. In addition, AI infrastructure development by technology providers is projected to contribute an additional $401 billion in spending as companies build scalable AI foundations.
The report notes that artificial intelligence is expected to remain in the “Trough of Disillusionment” through 2026, meaning enterprises are more likely to adopt AI through existing software vendors rather than launching entirely new, experimental projects. Improved predictability of return on investment will be critical before AI can be deployed at scale across organisations.
Separate research underscores the growing pressure on global infrastructure. A recent study estimates that at least $2 trillion in annual revenue will be required to fund the computing power needed to meet global AI demand by 2030. Despite anticipated AI-driven efficiency gains, the world still faces an estimated $800 billion funding gap to keep pace with rising demand.
By 2030, global incremental AI computing requirements could reach nearly 200 gigawatts, with the United States expected to account for roughly half of the total power demand. This surge reflects the rapid expansion of AI workloads across industries.
While computational demands continue to rise, leading enterprises have already begun moving beyond pilot projects. Companies that have successfully scaled AI across core workflows are reporting earnings before interest, taxes, depreciation, and amortization gains of 10 to 25 per cent over the past two years, demonstrating AI’s growing role as a driver of profitability rather than experimentation.
The findings suggest that the next phase of AI growth will be defined less by hype and more by disciplined investment, measurable outcomes, and infrastructure readiness across global markets.
